diff --git a/module2/exo1/toy_document_orgmode_python_en.org b/module2/exo1/toy_document_orgmode_python_en.org
index 11970068fa52c62672daefb9a36a6af112e32ea4..5f0f8a284840b16ea1f9cf29854ed655255a8791 100644
--- a/module2/exo1/toy_document_orgmode_python_en.org
+++ b/module2/exo1/toy_document_orgmode_python_en.org
@@ -1,32 +1,30 @@
#+TITLE: On the computation of pi
-#+AUTHOR: Anton Y.
-# #+DATE: 2025-07-07
#+LANGUAGE: en
-# #+PROPERTY: header-args :eval never-export
#+HTML_HEAD:
-# #+HTML_HEAD:
-# #+HTML_HEAD:
-# #+HTML_HEAD:
-# #+HTML_HEAD:
+#+HTML_HEAD:
+#+HTML_HEAD:
+#+HTML_HEAD:
+#+HTML_HEAD:
#+HTML_HEAD:
-* Asking the math library
+#+PROPERTY: header-args :session :exports both
-My computer tells me that π is approximatively
+* Asking the math library
+My computer tells me that $\pi$ is /approximatively/
-#+begin_src python :results output :session :exports both
+#+begin_src python :results value :session *python* :exports both
from math import *
pi
#+end_src
#+RESULTS:
+: 3.141592653589793
* * Buffon's needle
+Applying the method of [[https://en.wikipedia.org/wiki/Buffon%2527s_needle_problem][Buffon's needle]], we get the *approximation*
-Applying the method of Buffon's needle, we get the approximation
-
-#+begin_src python :results output :session :exports both
+#+begin_src python :results value :session *python* :exports both
import numpy as np
np.random.seed(seed=42)
N = 10000
@@ -36,15 +34,15 @@ theta = np.random.uniform(size=N, low=0, high=pi/2)
#+end_src
#+RESULTS:
+: 3.128911138923655
* Using a surface fraction argument
+A method that is easier to understand and does not make use of the
+$\sin$ function is based on the fact that if $X\sim U(0,1)$ and $Y\sim
+U(0,1)$, then $P[X^2+Y^2\leq 1] = \pi/4$ (see [[https://en.wikipedia.org/wiki/Monte_Carlo_method]["Monte Carlo method" on
+Wikipedia]]). The following code uses this approach:
-A method that is easier to understand and does not make use of the sin
-function is based on the fact that if X∼U(0,1) and Y∼U(0,1), then
-P[X2+Y2≤1]=π/4 (see "Monte Carlo method" on Wikipedia). The following
-code uses this approach:
-
-#+begin_src python :results file :session :var matplot_lib_filename=(org-babel-temp-file "figure" ".png") :exports both
+#+begin_src python :results output file :var matplot_lib_filename="figure_pi_mc2.png" :exports both :session *python*
import matplotlib.pyplot as plt
np.random.seed(seed=42)
@@ -65,13 +63,13 @@ print(matplot_lib_filename)
#+end_src
#+RESULTS:
-[[file:None]]
+[[file:figure_pi_mc2.png]]
-It is then straightforward to obtain a (not really good) approximation to π
- by counting how many times, on average, X2+Y2
- is smaller than 1:
+It is then straightforward to obtain a (not really good) approximation
+to $\pi$ by counting how many times, on average, $X^2 + Y^2$ is smaller
+than 1:
-#+begin_src python :results output :session :exports both
+#+begin_src python :results output :session *python* :exports both
4*np.mean(accept)
#+end_src